Patrik Edén

High-Energy-Physics Event Generation with PYTHIA 6.1

Pythia version 6 represents a merger of the Pythia 5, Jetset 7 and SPythia programs, with many improvements. It can be used to generate high-energy-physics ‘events’, i.e. sets of outgoing particles produced in the interactions between two incoming particles. The objective is to provide as accurate as possible a representation of event properties in a wide range of reactions. The underlying physics is not understood well enough to give an exact description; the programs therefore contain a combination of analytical results and various models. The emphasis in this article is on new aspects, but a few words of general introduction are included. Further documentation is available on the web.

Diagnostic and prognostic gene expression signatures in 177 soft tissue sarcomas: hypoxia-induced transcription profile signifies metastatic potential

BackgroundSoft tissue sarcoma (STS) diagnosis is challenging because of a multitude of histopathological subtypes, different genetic characteristics, and frequent intratumoral pleomorphism. One-third of STS metastasize and current risk-stratification is suboptimal, therefore, novel diagnostic and prognostic markers would be clinically valuable. We assessed the diagnostic and prognostic value of array-based gene expression profiles using 27 k cDNA microarrays in 177, mainly high-grade, STS of 13 histopathological subtypes.ResultsUnsupervised analysis resulted in two major clusters – one mainly containing STS characterized by type-specific genetic alterations and the other with a predominance of genetically complex and pleomorphic STS. Synovial sarcomas, myxoid/round-cell liposarcomas, and gastrointestinal stromal tumors clustered tightly within the former cluster and discriminatory signatures for these were characterized by developmental genes from the EGFR, FGFR, Wnt, Notch, Hedgehog, RAR and KIT signaling pathways. The more pleomorphic STS subtypes, e.g. leiomyosarcoma, malignant fibrous histiocytoma/undifferentiated pleomorphic sarcoma and dedifferentiated/pleomorphic liposarcoma, were part of the latter cluster and were characterized by relatively heterogeneous profiles, although subclusters herein were identified. A prognostic signature partly characterized by hypoxia-related genes was identified among 89 genetically complex pleomorphic primary STS and could, in a multivariate analysis including established prognostic markers, independently predict the risk of metastasis with a hazard ratio of 2.2 (P = 0.04).ConclusionDiagnostic gene expression profiles linking signaling pathways to the different STS subtypes were demonstrated and a hypoxia-induced metastatic profile was identified in the pleomorphic, high-grade STS. These findings verify diagnostic utility and application of expression data for improved selection of high-risk STS patients.

Estrogen receptor beta expression is associated with tamoxifen response in ER alpha-negative breast carcinoma

Purpose: Endocrine therapies, such as tamoxifen, are commonly given to most patients with estrogen receptor (ERα)–positive breast carcinoma but are not indicated for persons with ERα-negative cancer. The factors responsible for response to tamoxifen in 5% to 10% of patients with ERα-negative tumors are not clear. The aim of the present study was to elucidate the biology and prognostic role of the second ER, ERβ, in patients treated with adjuvant tamoxifen. Experimental Design: We investigated ERβ by immunohistochemistry in 353 stage II primary breast tumors from patients treated with 2 years adjuvant tamoxifen, and generated gene expression profiles for a representative subset of 88 tumors. Results: ERβ was associated with increased survival (distant disease-free survival, P = 0.01; overall survival, P = 0.22), and in particular within ERα-negative patients (P = 0.003; P = 0.04), but not in the ERα-positive subgroup (P = 0.49; P = 0.88). Lack of ERβ conferred early relapse (hazard ratio, 14; 95% confidence interval, 1.8-106; P = 0.01) within the ERα-negative subgroup even after adjustment for other markers. ERα was an independent marker only within the ERβ-negative tumors (hazard ratio, 0.44; 95% confidence interval, 0.21-0.89; P = 0.02). An ERβ gene expression profile was identified and was markedly different from the ERα signature. Conclusion: Expression of ERβ is an independent marker for favorable prognosis after adjuvant tamoxifen treatment in ERα-negative breast cancer patients and involves a gene expression program distinct from ERα. These results may be highly clinically significant, because in the United States alone, ∼10,000 women are diagnosed annually with ERα-negative/ERβ-positive breast carcinoma and may benefit from adjuvant tamoxifen.

Microarray-based classification of a consecutive series of 121 childhood acute leukemias: prediction of leukemic and genetic subtype as well as of minimal residual disease status.

Gene expression analyses were performed on 121 consecutive childhood leukemias (87 B-lineage acute lymphoblastic leukemias (ALLs), 11 T-cell ALLs and 23 acute myeloid leukemias (AMLs)), investigated during an 8-year period at a single center. The supervised learning algorithm k-nearest neighbor was utilized to build gene expression predictors that could classify the ALLs/AMLs according to clinically important subtypes with high accuracy. Validation experiments in an independent data set verified the high prediction accuracies of our classifiers. B-lineage ALLs with uncharacteristic cytogenetic aberrations or with a normal karyotype displayed heterogeneous gene expression profiles, resulting in low prediction accuracies. Minimal residual disease status (MRD) in T-cell ALLs with a high (>0.1%) MRD at day 29 could be classified with 100% accuracy already at the time of diagnosis. In pediatric leukemias with uncharacteristic cytogenetic aberrations or with a normal karyotype, unsupervised analysis identified two novel subgroups: one consisting mainly of cases remaining in complete remission (CR) and one containing a few patients in CR and all but one of the patients who relapsed. This study of a consecutive series of childhood leukemias confirms and extends further previous reports demonstrating that global gene expression profiling provides a valuable tool for genetic and clinical classification of childhood leukemias.

Comparing functional annotation analyses with Catmap

BackgroundRanked gene lists from microarray experiments are usually analysed by assigning significance to predefined gene categories, e.g., based on functional annotations. Tools performing such analyses are often restricted to a category score based on a cutoff in the ranked list and a significance calculation based on random gene permutations as null hypothesis.ResultsWe analysed three publicly available data sets, in each of which samples were divided in two classes and genes ranked according to their correlation to class labels. We developed a program, Catmap (available for download at http://bioinfo.thep.lu.se/Catmap), to compare different scores and null hypotheses in gene category analysis, using Gene Ontology annotations for category definition. When a cutoff-based score was used, results depended strongly on the choice of cutoff, introducing an arbitrariness in the analysis. Comparing results using random gene permutations and random sample permutations, respectively, we found that the assigned significance of a category depended strongly on the choice of null hypothesis. Compared to sample label permutations, gene permutations gave much smaller p-values for large categories with many coexpressed genes.ConclusionsIn gene category analyses of ranked gene lists, a cutoff independent score is preferable. The choice of null hypothesis is very important; random gene permutations does not work well as an approximation to sample label permutations.

Gene expression profiling of leukemic cell lines reveals conserved molecular signatures among subtypes with specific genetic aberrations

Hematologic malignancies are characterized by fusion genes of biological/clinical importance. Immortalized cell lines with such aberrations are today widely used to model different aspects of leukemogenesis. Using cDNA microarrays, we determined the gene expression profiles of 40 cell lines as well as of primary leukemias harboring 11q23/MLL rearrangements, t(1;19)[TCF3/PBX1], t(12;21)[ETV6/RUNX1], t(8;21)[RUNX1/CBFA2T1], t(8;14)[IGH@/MYC], t(8;14)[TRA@/MYC], t(9;22)[BCR/ABL1], t(10;11)[PICALM/MLLT10], t(15;17)[PML/RARA], or inv(16)[CBFB/MYH11]. Unsupervised classification revealed that hematopoietic cell lines of diverse origin, but with the same primary genetic changes, segregated together, suggesting that pathogenetically important regulatory networks remain conserved despite numerous passages. Moreover, primary leukemias cosegregated with cell lines carrying identical genetic rearrangements, further supporting that critical regulatory pathways remain intact in hematopoietic cell lines. Transcriptional signatures correlating with clinical subtypes/primary genetic changes were identified and annotated based on their biological/molecular properties and chromosomal localization. Furthermore, the expression profile of tyrosine kinase-encoding genes was investigated, identifying several differentially expressed members, segregating with primary genetic changes, which may be targeted with tyrosine kinase inhibitors. The identified conserved signatures are likely to reflect regulatory networks of importance for the transforming abilities of the primary genetic changes and offer important pathogenetic insights as well as a number of targets for future rational drug design.

Gene expression profiles relate to SS18/SSX fusion type in synovial sarcoma

We applied 27k spotted cDNA microarray slides to assess gene expression profiles in 26 samples from 24 patients with synovial sarcomas (SS). The data were analyzed in relation to histopathologic type, cytogenetic aberrations, gene fusion type and development of distant metastases. Supervised analysis based on gene fusion type in 12 SS with SS18/SSX1 and 9 with SS18/SSX2 revealed significant differences in gene expression profiles. Among the discriminators were several genes that have previously been found to be upregulated in SS, including AXL, ZIC2, SPAG7, AGRN, FOXC1, NCAM1 and multiple metallothioneins. Histopathology and degree of cytogenetic complexity did not significantly influence expression, whereas a genetic signature that related to development of metastases could be discerned, albeit with a high false‐positive rate. In conclusion, our findings demonstrate differentially expressed genes for the 2 major gene fusion variants in SS, SS18/SSX1 and SS18/SSX2, and thereby suggest that these result in different downstream effects.

SOX11 and TP53 add prognostic information to MIPI in a homogenously treated cohort of mantle cell lymphoma – a Nordic Lymphoma Group study

Mantle cell lymphoma (MCL) is an aggressive B cell lymphoma, where survival has been remarkably improved by use of protocols including high dose cytarabine, rituximab and autologous stem cell transplantation, such as the Nordic MCL2/3 protocols. In 2008, a MCL international prognostic index (MIPI) was created to enable stratification of the clinical diverse MCL patients into three risk groups. So far, use of the MIPI in clinical routine has been limited, as it has been shown that it inadequately separates low and intermediate risk group patients. To improve outcome and minimize treatment‐related morbidity, additional parameters need to be evaluated to enable risk‐adapted treatment selection. We have investigated the individual prognostic role of the MIPI and molecular markers including SOX11, TP53 (p53), MKI67 (Ki‐67) and CCND1 (cyclin D1). Furthermore, we explored the possibility of creating an improved prognostic tool by combining the MIPI with information on molecular markers. SOX11 was shown to significantly add prognostic information to the MIPI, but in multivariate analysis TP53 was the only significant independent molecular marker. Based on these findings, we propose that TP53 and SOX11 should routinely be assessed and that a combined TP53/MIPI score may be used to guide treatment decisions.

Pulsatile blood flow, shear force, energy dissipation and Murray's Law

BackgroundMurrays Law states that, when a parent blood vessel branches into daughter vessels, the cube of the radius of the parent vessel is equal to the sum of the cubes of the radii of daughter blood vessels. Murray derived this law by defining a cost function that is the sum of the energy cost of the blood in a vessel and the energy cost of pumping blood through the vessel. The cost is minimized when vessel radii are consistent with Murrays Law. This law has also been derived from the hypothesis that the shear force of moving blood on the inner walls of vessels is constant throughout the vascular system. However, this derivation, like Murrays earlier derivation, is based on the assumption of constant blood flow.MethodsTo determine the implications of the constant shear force hypothesis and to extend Murrays energy cost minimization to the pulsatile arterial system, a model of pulsatile flow in an elastic tube is analyzed. A new and exact solution for flow velocity, blood flow rate and shear force is derived.ResultsFor medium and small arteries with pulsatile flow, Murrays energy minimization leads to Murrays Law. Furthermore, the hypothesis that the maximum shear force during the cycle of pulsatile flow is constant throughout the arterial system implies that Murrays Law is approximately true. The approximation is good for all but the largest vessels (aorta and its major branches) of the arterial system.ConclusionA cellular mechanism that senses shear force at the inner wall of a blood vessel and triggers remodeling that increases the circumference of the wall when a shear force threshold is exceeded would result in the observed scaling of vessel radii described by Murrays Law.

Expression profiling to predict outcome in breast cancer: the influence of sample selection

Gene expression profiling of tumors using DNA microarrays is a promising method for predicting prognosis and treatment response in cancer patients. It was recently reported that expression profiles of sporadic breast cancers could be used to predict disease recurrence better than currently available clinical and histopathological prognostic factors. Having observed an overlap in those data between the genes that predict outcome and those that predict estrogen receptor-α status, we examined their predictive power in an independent data set. We conclude that it may be important to define prognostic expression profiles separately for estrogen receptor-α-positive and estrogen receptor-α-negative tumors.